Music recommendation has been around for sometime. Music recommendation systems and services, such as those known as Pandora, Ringo, Spotify, Musicovery, Steremood, are becoming increasingly popular ways for users to find and listen to music that may be of interest to them. Most of these music recommendation systems may identify and recommend a music to a user based on the user's personal preference, which may be indicated by the user through manual selection or some other type of affirmative action by the user to indicate the user's preferences (e.g., hitting a “like” or “dislike” button).
For example, Pandora is a personalized internet radio service. The service plays musical selections of a certain genre based on an artist selection by a user or subscriber of the service. To improve the music recommendation system over time, the user can provide positive or negative feedback for songs chosen by the service, which are taken into account when Pandora selects or recommends future songs to the user.
Ringo is another music recommendation system that may be accessed by users via email. Users may rate musical artists and then may be able to receive recommendations for further songs to listen to.
Spotify is yet another way to enjoy music socially. Spotify may not recommend songs based on individual preferences, but Spotify may instead allow registered users to integrate their user account with other social accounts (e.g., Facebook and Twitter accounts). Once a user integrates his or her Spotify account with other social media profiles, the user may access favorite music and playlists of his or her friends. Further, Spotify allows the user to share songs and playlists with his or her friends, and even work together on collaborative playlists.
Musicovery is yet another music recommendation system that has a collection of songs in its “Mood Radio”. On a homepage, music may be marked with one of four basic moods: Dark, energetic, positive, and calm. A user may choose his or her era, and share his or her mood with his or her favorite songs.
Steremood is yet another music recommendation system that may set “tags” to represent a variety of emotions. Users can choose from tags that most accurately define their emotional state.
However, some existing music recommendation systems and services such as those mentioned above may be relatively inflexible, since they may not take into account the fact that music preferences of a user using a mobile device may change over time as physical conditions of the user changes. Mobile device users often use their devices on the go while engaging in various activities and entering various environments, thus their music listening preferences may change from moment to moment. Requiring users to manually set or change their personal music listening preferences on their mobile devices can be inconvenient, as user preferences may change frequently among different activities or environments. Further, the limited user interface provided by most mobile devices may make manual setting more inconvenient. Accordingly, there exists a need for a music recommendation system or service that better considers the changing music preferences of a user.